{"id":"https://openalex.org/W2920518554","doi":"https://doi.org/10.1109/tencon.2018.8650098","title":"A Robust System for Visual Pattern Recognition in Engineering Drawing Documents","display_name":"A Robust System for Visual Pattern Recognition in Engineering Drawing Documents","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2920518554","doi":"https://doi.org/10.1109/tencon.2018.8650098","mag":"2920518554"},"language":"en","primary_location":{"id":"doi:10.1109/tencon.2018.8650098","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon.2018.8650098","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2018 - 2018 IEEE Region 10 Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103453088","display_name":"Purnendu Banerjee","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Purnendu Banerjee","raw_affiliation_strings":["ARC Document Solutions, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"ARC Document Solutions, Kolkata, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049952866","display_name":"Avinash Patel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Avinash Patel","raw_affiliation_strings":["ARC Document Solutions, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"ARC Document Solutions, Kolkata, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027598019","display_name":"Supriya Das","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Supriya Das","raw_affiliation_strings":["ARC Document Solutions, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"ARC Document Solutions, Kolkata, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016931742","display_name":"Bhagesh Seraogi","orcid":"https://orcid.org/0000-0002-2831-6029"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bhagesh Seraogi","raw_affiliation_strings":["ARC Document Solutions, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"ARC Document Solutions, Kolkata, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083258901","display_name":"Rahul Roy","orcid":"https://orcid.org/0000-0002-4026-1307"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rahul Roy","raw_affiliation_strings":["ARC Document Solutions, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"ARC Document Solutions, Kolkata, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049502948","display_name":"Himadri Majumder","orcid":"https://orcid.org/0000-0002-5059-5984"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Himadri Majumder","raw_affiliation_strings":["ARC Document Solutions, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"ARC Document Solutions, Kolkata, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113707271","display_name":"Srinivas Mukkamala","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Srinivas Mukkamala","raw_affiliation_strings":["ARC Document Solutions, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"ARC Document Solutions, Kolkata, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025093894","display_name":"B.B. Chaudhuri","orcid":"https://orcid.org/0000-0003-0297-8929"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"B. B. Chaudhuri","raw_affiliation_strings":["CVPR Unit, Indian Statistical Institute, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"CVPR Unit, Indian Statistical Institute, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5103453088"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1045,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49241165,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"19","issue":null,"first_page":"2050","last_page":"2055"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/curvature","display_name":"Curvature","score":0.7031381726264954},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6348236799240112},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6172021627426147},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5660262703895569},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.561039388179779},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.5528898239135742},{"id":"https://openalex.org/keywords/inflection-point","display_name":"Inflection point","score":0.5446847677230835},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5268570184707642},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5114809274673462},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49162203073501587},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.48147904872894287},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.476694792509079},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.4492201507091522},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4353449046611786},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.42692720890045166},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4156690537929535},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34182149171829224},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29570263624191284},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.12782993912696838}],"concepts":[{"id":"https://openalex.org/C195065555","wikidata":"https://www.wikidata.org/wiki/Q214881","display_name":"Curvature","level":2,"score":0.7031381726264954},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6348236799240112},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6172021627426147},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5660262703895569},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.561039388179779},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.5528898239135742},{"id":"https://openalex.org/C74545648","wikidata":"https://www.wikidata.org/wiki/Q212794","display_name":"Inflection point","level":2,"score":0.5446847677230835},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5268570184707642},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5114809274673462},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49162203073501587},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.48147904872894287},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.476694792509079},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.4492201507091522},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4353449046611786},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.42692720890045166},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4156690537929535},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34182149171829224},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29570263624191284},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.12782993912696838},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon.2018.8650098","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon.2018.8650098","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2018 - 2018 IEEE Region 10 Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1491319300","https://openalex.org/W1532362218","https://openalex.org/W1627400044","https://openalex.org/W2065429801","https://openalex.org/W2072738093","https://openalex.org/W2111308925","https://openalex.org/W2114785422","https://openalex.org/W2119605622","https://openalex.org/W2130103520","https://openalex.org/W2143802725","https://openalex.org/W2150144148","https://openalex.org/W2151103935","https://openalex.org/W2159498975","https://openalex.org/W2161969291","https://openalex.org/W4285719527","https://openalex.org/W6631707545","https://openalex.org/W6681024905","https://openalex.org/W6683344514"],"related_works":["https://openalex.org/W2375684291","https://openalex.org/W2361205043","https://openalex.org/W2354676191","https://openalex.org/W3188646203","https://openalex.org/W2023911433","https://openalex.org/W136674370","https://openalex.org/W2909957174","https://openalex.org/W2105527480","https://openalex.org/W2013485381","https://openalex.org/W637977166"],"abstract_inverted_index":{"In":[0],"AEC":[1,254],"(Architectural,":[2],"Engineering":[3],"and":[4,24,34,151,174,200,209,259],"Constructional)":[5],"domain,":[6],"the":[7,74,78,81,91,101,107,112,118,138,144,162,177,181,189,211,214,228,260,270,285],"architects":[8],"use":[9,122],"several":[10],"types":[11],"of":[12,18,21,57,77,80,143,149,180,188,217,237,253,256,280,282],"drawing":[13,257],"documents.":[14,58,283],"These":[15],"documents":[16,258],"consist":[17],"various":[19],"category":[20],"graphical":[22],"objects":[23,26,53,145,275],"such":[25],"can":[27,48,287],"be":[28,49,288],"classified":[29],"based":[30,72,99,185],"on":[31,73,100,106,117,250],"their":[32,201],"shape":[33,139,179,186],"curvature":[35,102,141,171],"properties.":[36],"Here,":[37],"we":[38,64,87,110,121,153,166],"have":[39,65,154,167,221,246],"proposed":[40,266],"a":[41,55,67,169,224,232,242,251,277],"query":[42,229],"enabled":[43],"image":[44],"searching":[45],"system":[46,249,267],"which":[47],"used":[50,206,289],"to":[51,89,131,175,207,226,272],"locate":[52,273],"in":[54],"set":[56],"To":[59,136,160],"achieve":[60],"our":[61,132,248],"goal,":[62],"at-first":[63],"identified":[66],"key":[68,129,215],"point":[69,116],"search":[70],"window":[71,86],"inflection":[75],"points":[76,124,216],"contour":[79,191],"object.":[82,244],"Then,":[83],"for":[84,241,290],"each":[85],"try":[88],"classify":[90],"curve":[92],"segment":[93],"into":[94],"positive":[95],"or":[96,114],"negative":[97],"class":[98,255],"values.":[103],"Then":[104],"depending":[105],"predicted":[108],"class,":[109],"get":[111,161],"maxima":[113],"minima":[115],"contour.":[119],"Now,":[120],"these":[123,195],"as":[125,231],"seed":[126],"values":[127],"(initial":[128],"points)":[130],"feature":[133,157,164,203],"detection":[134],"mechanism.":[135],"extract":[137],"and/or":[140],"properties":[142],"at":[146],"different":[147],"levels":[148],"scale":[150],"orientation,":[152],"employed":[155],"two":[156,196,218],"extraction":[158,172],"mechanisms.":[159],"local":[163],"descriptor,":[165],"introduced":[168,223],"neighborhood-based":[170],"methodology":[173],"consider":[176],"global":[178],"object,":[182],"Hu":[183],"moments":[184],"descriptor":[187],"object":[190,230,291],"is":[192,205],"computed.":[193],"Finally,":[194],"features":[197],"are":[198,262],"normalized,":[199],"combined":[202],"vector":[204],"compare":[208],"measure":[210],"similarity":[212],"between":[213],"objects.":[219],"We":[220,245],"also":[222],"mechanism":[225],"identify":[227],"whole,":[233],"when":[234],"it":[235],"consists":[236],"multiple":[238],"overlapping":[239],"contours":[240],"single":[243],"tested":[247],"variety":[252],"results":[261],"quite":[263],"encouraging.":[264],"The":[265],"will":[268],"enable":[269],"users":[271],"similar":[274],"inside":[276],"project":[278],"consisting":[279],"hundreds":[281],"Also,":[284],"method":[286],"hyperlinking":[292],"with":[293],"some":[294],"alterations.":[295]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}